## Abstract

A 2-part latent growth model can be used to analyze semicontinuous data to simultaneously study change in the probability that an individual engages in a behavior, and if engaged, change in the behavior. This article uses a Monte Carlo (MC) integration algorithm to study the interrelationships between the growth factors of 2 variables measured longitudinally where each variable can follow a 2-part latent growth model. A SAS macro implementing Mplus is developed to estimate the model to take into account the sampling uncertainty of this simulation-based computational approach. A sample of time-use data is used to show how maximum likelihood estimates can be obtained using a rectangular numerical integration method and an MC integration method.

Original language | English (US) |
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Pages (from-to) | 131-148 |

Number of pages | 18 |

Journal | Structural Equation Modeling |

Volume | 21 |

Issue number | 1 |

DOIs | |

State | Published - Jan 2014 |

## Keywords

- Monte Carlo integration
- longitudinal semicontinuous variables
- multivariate two-part latent growth curve model

## ASJC Scopus subject areas

- Decision Sciences(all)
- Modeling and Simulation
- Sociology and Political Science
- Economics, Econometrics and Finance(all)